Microfluidic SERS devices: brightening the future of bioanalysis.

A new avenue has opened up for applications of surface-enhanced Raman spectroscopy (SERS) in the biomedical field, mainly due to the striking advantages offered by SERS tags. SERS tags provide indirect identification of analytes with rich and highly specific spectral fingerprint information, high sensitivity, and outstanding multiplexing potential, making them very useful in in vitro and in vivo assays. The recent and innovative advances in nanomaterial science, novel Raman reporters, and emerging bioconjugation protocols have helped develop ultra-bright SERS tags as powerful tools for multiplex SERS-based detection and diagnosis applications. Nevertheless, to translate SERS platforms to real-world problems, some challenges, especially for clinical applications, must be addressed. This review presents the current understanding of the factors influencing the quality of SERS tags and the strategies commonly employed to improve not only spectral quality but the specificity and reproducibility of the interaction of the analyte with the target ligand. It further explores some of the most common approaches which have emerged for coupling SERS with microfluidic technologies, for biomedical applications. The importance of understanding microfluidic production and characterisation to yield excellent device quality while ensuring high throughput production are emphasised and explored, after which, the challenges and approaches developed to fulfil the potential that SERS-based microfluidics have to offer are described.

Glycaemic control during the COVID-19 pandemic: A catastrophe or a sign of hope for the person with type 1 Diabetes Mellitus? Control glucémico en tiempos de pandemia por COVID-19: ¿Una catástrofe o un signo de esperanza para la persona con diabetes mellitus tipo 1?

Introduction In a person with type 1 diabetes, any change concerning daily routine may lead to changes in glycaemic control. This study aimed to evaluate the impact of work and lockdown on glycaemic control in adults with type 1 diabetes. Material and methods A retrospective cohort was stratified into three activity groups (g1-students/telework/laid-off;g2-unemployed/retired;g3-work without lockdown). Continuous and categorical variations (reductions ≥ 0.4%) in glycated haemoglobin were obtained in 2020 (t3:December/2019–March/2020;t4:April/2020–July/2020) and in homologous periods of 2019. Intragroup comparisons between years and intergroups in the same year were made. Regression models were developed to predict the variation of glycated haemoglobin in 2020. Results 241 participants were included, with a significant reduction between t4 and t3 (vs. t2 and t1) in g1 (p < 0.001) and g2 (p = 0.025) and in 2020 in g1 (vs. g2, p < 0.001;vs. g3, p < 0.001). Only g1 presented superiority in the reduction ≥0.4% in glycated haemoglobin in 2020 (vs. 2019, p < 0.001;vs. g2, p < 0.001;vs. g3, p < 0.001). The insulin regimens were comparable and the development of hypoglycaemia was found to be superimposed between t3 and t4, except for g1, which was higher at t3 (p = 0.029). G1 correlated with continuous reductions (vs. g2, p = 0.001;vs. g3, p < 0.001) and ≥0.4% in glycated haemoglobin in 2020 (vs. g2, OR 3.6, p < 0.001;vs. g3, OR 12.7, p < 0.001), regardless of the age and duration of type 1 diabetes. Conclusions A more stable and better glycaemic control was observed in participants who transitioned from face-to-face work to total lockdown.

Glycaemic control during the COVID-19 pandemic: A catastrophe or a sign of hope for the person with type 1 Diabetes Mellitus?

Introduction: In a person with type 1 diabetes, any change concerning daily routine may lead to changes in glycaemic control. This study aimed to evaluate the impact of work and lockdown on glycaemic control in adults with type 1 diabetes. Material and methods: A retrospective cohort was stratified into three activity groups (g1-students/telework/laid-off; g2-unemployed/retired; g3-work without lockdown). Continuous and categorical variations (reductions ≥ 0.4%) in glycated haemoglobin were obtained in 2020 (t3:December/2019-March/2020; t4:April/2020-July/2020) and in homologous periods of 2019. Intragroup comparisons between years and intergroups in the same year were made. Regression models were developed to predict the variation of glycated haemoglobin in 2020. Results: 241 participants were included, with a significant reduction between t4 and t3 (vs. t2 and t1) in g1 (p < 0.001) and g2 (p = 0.025) and in 2020 in g1 (vs. g2, p < 0.001; vs. g3, p < 0.001). Only g1 presented superiority in the reduction ≥0.4% in glycated haemoglobin in 2020 (vs. 2019, p < 0.001; vs. g2, p < 0.001; vs. g3, p < 0.001). The insulin regimens were comparable and the development of hypoglycaemia was found to be superimposed between t3 and t4, except for g1, which was higher at t3 (p = 0.029). G1 correlated with continuous reductions (vs. g2, p = 0.001; vs. g3, p < 0.001) and ≥0.4% in glycated haemoglobin in 2020 (vs. g2, OR 3.6, p < 0.001; vs. g3, OR 12.7, p < 0.001), regardless of the age and duration of type 1 diabetes. Conclusions: A more stable and better glycaemic control was observed in participants who transitioned from face-to-face work to total lockdown.

Introducción: En una persona con diabetes tipo 1, cualquier cambio en la rutina diaria puede provocar cambios en el control glucémico. Este estudio tuvo como objetivo evaluar el impacto del trabajo y el confinamiento en el control glucémico en adultos con diabetes tipo 1. Material y métodos: Se estratificó una cohorte retrospectiva en tres grupos de actividad (g1-estudiantes/teletrabajo/despido; g2-desempleados/jubilados; g3-trabajo sin encierro). Se obtuvieron variaciones continuas y categóricas (reducciones ≥ 0,4%) en la hemoglobina glucosilada en 2020 (t3: diciembre/2019-marzo/2020; t4: abril/2020-julio/2020) y en períodos homólogos de 2019. Se desarrollaron modelos de regresión para predecir la variación de la hemoglobina glucosilada en 2020. Resultados: Se incluyeron 241 participantes, con una reducción significativa entre t4 y t3 (vs. t2 y t1) en g1 (p < 0,001) y g2 (p = 0,025) y en 2020 en g1 (vs. g2, p < 0,001; vs. g3, p < 0,001). Solo g1 demostró superioridad en la reducción ≥ 0,4% de la hemoglobina glucosilada en 2020 (vs. 2019, p < 0,001; vs. g2, p < 0,001; vs. g3, p < 0,001). Los regímenes de terapia con insulina fueron comparables y el desarrollo de hipoglucemia fue superponible entre t3 y t4, excepto para g1, que fue mayor en t3 (p = 0,029). G1 se correlacionó con reducciones continuas (vs. g2, p = 0,001; vs. g3, p < 0,001) y ≥ 0,4% en la hemoglobina glucosilada en 2020 (vs. g2, odds ratio [OR] 3,6, p < 0,001; vs. g3, OR 12,7, p < 0,001), independientemente de la edad y la duración de la diabetes tipo 1. Conclusiones: Se observó un control glucémico más optimizado a los participantes que pasaron del trabajo presencial al confinamiento total.

Control glucémico en tiempos de pandemia por COVID-19: ¿una catástrofe o un signo de esperanza para la persona con Diabetes Mellitus tipo 1? Glycaemic control during the COVID-19 pandemic: a catastrophe or a sign of hope for the person with type 1 Diabetes Mellitus?

Introducción: En una persona con diabetes tipo 1, cualquier cambio en la rutina diaria puede provocar cambios en el control glucémico. Este estudio tuvo como objetivo evaluar el impacto del trabajo y el confinamiento en el control glucémico en adultos con diabetes tipo 1. Material y métodos: Se estratificó una cohorte retrospectiva en tres grupos de actividad (g1-estudiantes/teletrabajo/despido;g2-desempleados/jubilados;g3-trabajo sin encierro). Se obtuvieron variaciones continuas y categóricas (reducciones ≥0,4%) en la hemoglobina glucosilada en 2020 (t3: diciembre/2019-marzo/2020;t4:abril/2020-julio/2020) y en períodos homólogos de 2019. Se desarrollaron modelos de regresión para predecir la variación de la hemoglobina glucosilada en 2020. Resultados: Se incluyeron 241 participantes, con una reducción significativa entre t4 y t3 (vs. t2 y t1) en g1 (p<0,001) y g2 (p=0,025) y en 2020 en g1 (vs. g2, p<0,001;vs. g3, p<0,001). Solo g1 demostró superioridad en la reducción ≥0,4% de la hemoglobina glucosilada en 2020 (vs. 2019, p <0,001;vs. g2, p<0,001;vs. g3, p<0,001). Los regímenes de terapia con insulina fueron comparables y se encontró que el desarrollo de hipoglucemia estaba superpuesto entre t3 y t4, excepto para g1, que fue mayor en t3 (p=0,029). G1 se correlacionó con reducciones continuas (vs. g2, p=0,001;vs. g3, p<0,001) y ≥0,4% en la hemoglobina glucosilada en 2020 (vs. g2, OR 3,6, p<0,001;vs. g3, OR 12,7, p<0,001), independientemente de la edad y la duración de la diabetes tipo 1. Conclusiones: Se apuntó un control glucémico más optimizado a los participantes que pasaron del trabajo presencial al confinamiento total.

The Influence of Vitamin D Status on the Severity of SARS-CoV-2 Respiratory Infection

Introduction: The high prevalence of vitamin D (vitD) deficiency in the general population is well recognized. Evidence suggests an immunomodulatory role for vitD in pro-inflammatory conditions, but doubt remains on its association with the severity of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) respiratory infection (RI).